STEAR: Robust Step Counting from Earables

Jay Prakash, Zhijian Yang, Yu Lin Wei, Romit Roy Choudhury

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper shows that inertial measurement units (IMUs) inside earphones offer a clear advantage in counting the number of steps a user has walked. While step-count has been extensively studied in the mobile computing community, there is wide consensus that false positives are common. The main reason for false positives is due to limb and device motions producing the same periodic bounce as the human walk. However, when IMUs are at the ear, we find that many of the lower-body motions are naturally "filtered out", i.e., these noisy motions do not propagate all the way up to the ear. Hence, the earphone IMU detects a bounce produced only from walking. While head movements can still pollute this bouncing signal, we develop methods to alleviate the problem. Results show 95% step-count accuracy even in the most difficult test case-very slow walk-where smartphone and fitbit-like systems falter. Importantly, our system STEAR is robust to changes in walking patterns and scales well across different users. Additionally, we demonstrate how STEAR also bring opportunities for effective jump analysis, often important for exercises and injury-related rehabilitation.

Original languageEnglish (US)
Title of host publicationProceedings of the 1st International Workshop on Earable Computing, EarComp 2019
PublisherAssociation for Computing Machinery, Inc
Pages36-41
Number of pages6
ISBN (Electronic)9781450369022
DOIs
StatePublished - Sep 9 2019
Event1st International Workshop on Earable Computing, EarComp 2019 - London, United Kingdom
Duration: Sep 9 2019 → …

Publication series

NameProceedings of the 1st International Workshop on Earable Computing, EarComp 2019

Conference

Conference1st International Workshop on Earable Computing, EarComp 2019
CountryUnited Kingdom
CityLondon
Period9/9/19 → …

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Science Applications

Fingerprint Dive into the research topics of 'STEAR: Robust Step Counting from Earables'. Together they form a unique fingerprint.

  • Cite this

    Prakash, J., Yang, Z., Wei, Y. L., & Choudhury, R. R. (2019). STEAR: Robust Step Counting from Earables. In Proceedings of the 1st International Workshop on Earable Computing, EarComp 2019 (pp. 36-41). (Proceedings of the 1st International Workshop on Earable Computing, EarComp 2019). Association for Computing Machinery, Inc. https://doi.org/10.1145/3345615.3361133